A diagnosis of advanced, incurable cancer at different stages of the adult life span holds different meaning for patients, family members, providers, and society as well. Late stage cancer care and the shift from curative to palliative care for adult patients have become major challenges for health care providers. Studies to improve end-of-life care decision-making have been largely unsuccessful, yet results offer important clues for developing more effective supportive care interventions. This study proposes to test a coping and communication support (CCS) intervention for patients with incurable advanced stage cancer, over the period when goals of care may shift. An examination of intervention effects is proposed using a randomized clinical trial with patients stratified by age group in assignment to the CCS intervention group or usual care control group. Aging research argues for the importance of developing age-sensitive interventions, this will be the first study specifically designed to examine age group differences in such an intervention. The study will be implemented in two urban tertiary care - cancer clinics that reach underserved populations. Proposed hypotheses include: (1) main effects and age group interaction effects of the CCS intervention on advanced cancer care management and quality of life (QOL) for middle-aged (40-60; N = 176 in the intervention and 176 in the control group) and young-old patients (61-80; N = 176 in each group) at 6,12, and 18 months or to death if sooner; (2) age group differences in level of engagement in the CCS intervention (e.g., type, frequency of contact) and (3) age group differences in a model of association including background variables, mediating variables (engagement in CCS intervention and advanced cancer care practices) and quality of life outcomes. The primary analyses, using a multivariate generalized least squares approach, will test the age by intervention interaction and main effects on care practices and quality of life outcomes. Individual outcomes, adjusted for confounders, will be modeled separately. Repeated measures data will involve regression models using estimated slopes as dependent variables. Secondary analyses, using general linear models, will address the relationship between intervening variables and patient outcomes and include hazard models for analyzing time to hospice or death. Results from this study, will be disseminated to inform area-based care initiative.